# Hackathon Badge Claims — Plane Mode Scholar

**Build Small Hackathon · Backyard AI · June 2026**

## Badge stack (all merit badges)

| Badge | How we earn it |
|-------|----------------|
| **Well-Tuned** | LoRA SFT published: [GuusBouwensNL/plane-mode-nemotron-4b-study-coach](https://huggingface.co/GuusBouwensNL/plane-mode-nemotron-4b-study-coach) |
| **Llama Champion** | Fine-tuned model runs via `llama.cpp` (`./scripts/start_llamacpp.sh` + `--lora`) |
| **Off the Grid** | No cloud LLM APIs when `PMS_INFERENCE_BACKEND=llamacpp` — local `llama-server` only |
| **Off-Brand** | Custom `gr.Server` UI — `plane_mode_scholar/gradio_ui/static/index.html` |
| **Sharing is Caring** | Open traces: `docs/agent-traces-dataset.jsonl` + `/export_trace` |
| **Field Notes** | [docs/field-notes.md](field-notes.md) |

### Full local stack (demo video path)

```bash
# 1. Convert HF LoRA → GGUF LoRA (uses llama.cpp convert_lora_to_gguf.py)
python scripts/export_lora_gguf.py

# 2. Start llama-server: Nemotron 4B Q4_K_M + your study-coach LoRA
./scripts/start_llamacpp.sh

# 3. App (second terminal)
PMS_INFERENCE_BACKEND=llamacpp python app.py
```

Health check should show `"inference_backend": "llamacpp"` and `"lora_applied": true`.

### HF Space (public demo)

**Gradio SDK (default):** ZeroGPU + PEFT transformers — Well-Tuned badge on the public Space.

**Docker SDK (optional):** Embedded `llama-cpp-python` with GGUF + LoRA — all three local badges on Space. See [docs/space-llamacpp.md](space-llamacpp.md).

**Browser WebGPU:** [Llamas on the Web](https://reeselevine.github.io/llamas-on-the-web/) proves llama.cpp in the browser; LoRA in wllama is still roadmap — use merged GGUF or screen-record the local `llama-server` flow for judge demo.

## Evidence table

| Badge | Status | Evidence |
|-------|--------|----------|
| **Off the Grid** | ✅ | `PMS_INFERENCE_BACKEND=llamacpp` → local `llama-server`, no OpenAI/Anthropic APIs |
| **Off-Brand** | ✅ | Custom `gradio.Server` frontend inspired by [SwarmGrid](https://github.com/GJB99/SwarmGrid) |
| **Llama Champion** | ✅ | `scripts/start_llamacpp.sh`, `scripts/export_lora_gguf.py`, `core/llm_llamacpp.py` |
| **Sharing is Caring** | ✅ | `docs/agent-traces-dataset.jsonl` + `/export_trace` |
| **Field Notes** | ✅ | [docs/field-notes.md](field-notes.md) |
| **Well-Tuned** | ✅ | [GuusBouwensNL/plane-mode-nemotron-4b-study-coach](https://huggingface.co/GuusBouwensNL/plane-mode-nemotron-4b-study-coach) |
| **Best Agent** (award) | ✅ | `StudyAgent` monitor→plan→act — **FLY** button |
| **Nemotron Quest** | ✅ | Nemotron 3 Nano 4B (fine-tuned) + 30B fallback |

## Quick verification

```bash
curl -s localhost:7860/api/health | python3 -m json.tool
python scripts/export_lora_gguf.py --dry-run
python scripts/verify_finetuned_model.py
```

## UI modes

| Mode | Env | Use case |
|------|-----|----------|
| **Server (default)** | `PMS_SERVER_UI=true` | Hackathon demo — SwarmGrid-style dashboard |
| **Blocks (legacy)** | `PMS_USE_BLOCKS=true` | Full multi-tab feature surface |
| **llama.cpp** | `PMS_INFERENCE_BACKEND=llamacpp` | Badge stack: Well-Tuned + Llama Champion + Off the Grid |